Microstructural correlations of white matter tracts in the human brain

The purpose of this study is to investigate whether specific patterns of correlation exist in diffusion tensor imaging (DTI) parameters across different white matter tracts in the normal human brain, and whether the relative strengths of these putative microstructural correlations might reflect phylogenetic and functional similarities between tracts. We performed quantitative DTI fiber tracking on 44 healthy adult volunteers to obtain tract-based measures of mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) from four homologous pairs of neocortical association pathways (arcuate fasciculi, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate fasciculi bilaterally), a homologous pair of limbic association pathways (left and right dorsal cingulum bundles), and a homologous pair of cortical-subcortical projection pathways (left and right corticospinal tracts). From the resulting inter-tract correlation matrices, we show that there are statistically significant correlations of DTI parameters between tracts, and that there are statistically significant variations among these inter-tract correlations. Furthermore, we observe that many, but by no means all, of the strongest correlations are between homologous tracts in the left and right hemispheres. Even among homologous pairs of tracts, there are wide variations in the degree of coupling. Finally, we generate a data-driven hierarchical clustering of the fiber pathways based on pairwise FA correlations to demonstrate that the neocortical association pathways tend to group separately from the limbic pathways at trend-level statistical significance, and that the projection pathways of the left and right corticospinal tracts comprise the most distant outgroup with high confidence (p<0.01). Hence, specific patterns of microstructural correlation exist between tracts and may reflect phylogenetic and functional similarities between tracts. The study of these microstructural relationships between white matter pathways might aid research on the genetic basis and on the behavioral effects of axonal connectivity, as well as provide a revealing new perspective with which to investigate neurological and psychiatric disorders.

[1]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[3]  Y. Cohen,et al.  High b‐value q‐space analyzed diffusion‐weighted MRS and MRI in neuronal tissues – a technical review , 2002, NMR in biomedicine.

[4]  Osamu Abe,et al.  Tract-specific analysis of white matter pathways in healthy subjects: a pilot study using diffusion tensor MRI , 2009, Neuroradiology.

[5]  Bruce D. McCandliss,et al.  Extent of Microstructural White Matter Injury in Postconcussive Syndrome Correlates with Impaired Cognitive Reaction Time: A 3T Diffusion Tensor Imaging Study of Mild Traumatic Brain Injury , 2008, American Journal of Neuroradiology.

[6]  P. Basser,et al.  Axcaliber: A method for measuring axon diameter distribution from diffusion MRI , 2008, Magnetic resonance in medicine.

[7]  Alan Connelly,et al.  Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution , 2004, NeuroImage.

[8]  Hangyi Jiang,et al.  Pediatric diffusion tensor imaging: Normal database and observation of the white matter maturation in early childhood , 2006, NeuroImage.

[9]  Derek K. Jones,et al.  The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: A Monte Carlo study † , 2004, Magnetic resonance in medicine.

[10]  Erin D. Bigler,et al.  Diffusion tensor imaging of hemispheric asymmetries in the developing brain , 2009, Journal of clinical and experimental neuropsychology.

[11]  Hidetoshi Shimodaira,et al.  Approximately unbiased tests of regions using multistep-multiscale bootstrap resampling , 2004, math/0508602.

[12]  Duan Xu,et al.  Q‐ball reconstruction of multimodal fiber orientations using the spherical harmonic basis , 2006, Magnetic resonance in medicine.

[13]  Yaniv Assaf,et al.  A multivariate hypothesis testing framework for tissue clustering and classification of DTI data , 2009, NMR in biomedicine.

[14]  L Nyberg,et al.  Altered brain white matter integrity in healthy carriers of the APOE ε4 allele , 2006, Neurology.

[15]  S. Wakana,et al.  MRI Atlas of Human White Matter , 2005 .

[16]  John Russell,et al.  Dysmyelination Revealed through MRI as Increased Radial (but Unchanged Axial) Diffusion of Water , 2002, NeuroImage.

[17]  Dietmar Cordes,et al.  Role of the corpus callosum in functional connectivity. , 2003, AJNR. American journal of neuroradiology.

[18]  Hidetoshi Shimodaira.  An approximately unbiased test of phylogenetic tree selection. , 2002, Systematic biology.

[19]  A. Mayer,et al.  A prospective diffusion tensor imaging study in mild traumatic brain injury , 2010, Neurology.

[20]  Marco Catani,et al.  From hodology to function. , 2007, Brain : a journal of neurology.

[21]  Hangyi Jiang,et al.  DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking , 2006, Comput. Methods Programs Biomed..

[22]  Hidetoshi Shimodaira,et al.  Pvclust: an R package for assessing the uncertainty in hierarchical clustering , 2006, Bioinform..

[23]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[24]  Luis Concha,et al.  Imaging brain connectivity in children with diverse reading ability , 2005, NeuroImage.

[25]  John S. Duncan,et al.  Hemispheric asymmetries in language-related pathways: A combined functional MRI and tractography study , 2006, NeuroImage.

[26]  Randy L. Gollub,et al.  Reproducibility of quantitative tractography methods applied to cerebral white matter , 2007, NeuroImage.

[27]  Erick Jorge Canales-Rodríguez,et al.  Mathematical description of q‐space in spherical coordinates: Exact q‐ball imaging , 2009, Magnetic resonance in medicine.

[28]  A. Dale,et al.  Age-related alterations in white matter microstructure measured by diffusion tensor imaging , 2005, Neurobiology of Aging.

[29]  Zhizhou Wang,et al.  DTI segmentation using an information theoretic tensor dissimilarity measure , 2005, IEEE Transactions on Medical Imaging.

[30]  B. Miller,et al.  Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.

[31]  D. Tuch.  Q‐ball imaging , 2004, Magnetic resonance in medicine.

[32]  Carl-Fredrik Westin,et al.  Tract-based morphometry for white matter group analysis , 2009, NeuroImage.

[33]  Xiaoping P. Hu,et al.  Asymmetric connectivity reduction and its relationship to “HAROLD” in aging brain , 2009, Brain Research.

[34]  Carl-Fredrik Westin,et al.  QUANTITATIVE EXAMINATION OF A NOVEL CLUSTERING METHOD USING MAGNETIC RESONANCE DIFFUSION TENSOR TRACTOGRAPHY , 2008 .

[35]  A. C. Rencher.  Methods of multivariate analysis , 1995 .

[36]  Xavier Bresson,et al.  White matter fiber tract segmentation in DT-MRI using geometric flows , 2005, Medical Image Anal..

[37]  Alan C. Evans,et al.  Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. , 2007, Cerebral cortex.

[38]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[39]  Tianzi Jiang,et al.  Side and handedness effects on the cingulum from diffusion tensor imaging , 2005, Neuroreport.

[40]  A M McIntosh,et al.  The effects of a neuregulin 1 variant on white matter density and integrity , 2008, Molecular Psychiatry.

[41]  K. Lim,et al.  Age‐related decline in brain white matter anisotropy measured with spatially corrected echo‐planar diffusion tensor imaging , 2000, Magnetic resonance in medicine.

[42]  A. Snyder,et al.  Diffusion-tensor MR imaging of gray and white matter development during normal human brain maturation. , 2002, AJNR. American journal of neuroradiology.

[43]  Suyash P. Awate,et al.  A fuzzy, nonparametric segmentation framework for DTI and MRI analysis: with applications to DTI-tract extraction. , 2007, IEEE transactions on medical imaging.

[44]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[45]  Agatha D. Lee,et al.  Genetics of Brain Fiber Architecture and Intellectual Performance , 2009, The Journal of Neuroscience.

[46]  Ofer Pasternak,et al.  The effect of metric selection on the analysis of diffusion tensor MRI data , 2010, NeuroImage.

[47]  David M. Thomasson,et al.  Reliability of fiber tracking measurements in diffusion tensor imaging for longitudinal study , 2010, NeuroImage.

[48]  E. Smith.  Methods of Multivariate Analysis , 1997 .

[49]  John J Sidtis,et al.  Abnormal white matter integrity in healthy apolipoprotein E epsilon4 carriers , 2005, Neuroreport.

[50]  P. Hagmann,et al.  Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[51]  Pratik Mukherjee,et al.  Structural dissociation of attentional control and memory in adults with and without mild traumatic brain injury. , 2008, Brain : a journal of neurology.

[52]  Torsten Rohlfing,et al.  Problem Solving, Working Memory, and Motor Correlates of Association and Commissural Fiber Bundles in Normal Aging: a Quantitative Fiber Tracking Study , 2022 .

[53]  Bruce D. McCandliss,et al.  Left lateralized white matter microstructure accounts for individual differences in reading ability and disability , 2006, Neuropsychologia.

[54]  Derek K. Jones,et al.  Symmetries in human brain language pathways correlate with verbal recall , 2007, Proceedings of the National Academy of Sciences.

[55]  M. Catani.  Diffusion tensor magnetic resonance imaging tractography in cognitive disorders , 2006, Current opinion in neurology.

[56]  Peter Stoeter,et al.  Association of 5′ end neuregulin-1 (NRG1) gene variation with subcortical medial frontal microstructure in humans , 2008, NeuroImage.

[57]  Jie Tian,et al.  Robust unsupervised segmentation of infarct lesion from diffusion tensor MR images using multiscale statistical classification and partial volume voxel reclassification , 2004, NeuroImage.

[58]  Andrew L. Alexander,et al.  Hybrid diffusion imaging , 2007, NeuroImage.

[59]  Connie M. Borror,et al.  Methods of Multivariate Analysis, 2nd Ed. , 2004 .

[60]  Khader M Hasan,et al.  Retrospective measurement of the diffusion tensor eigenvalues from diffusion anisotropy and mean diffusivity in DTI , 2006, Magnetic resonance in medicine.

[61]  David Bonekamp,et al.  Diffusion tensor imaging in children and adolescents: Reproducibility, hemispheric, and age-related differences , 2007, NeuroImage.

[62]  L. Frank.  Anisotropy in high angular resolution diffusion‐weighted MRI , 2001, Magnetic resonance in medicine.

[63]  D. Reich,et al.  Quantitative characterization of the corticospinal tract at 3T. , 2006, AJNR. American journal of neuroradiology.

[64]  L Nyberg,et al.  Altered brain white matter integrity in healthy carriers of the APOE epsilon4 allele: a risk for AD? , 2006, Neurology.

[65]  David S Tuch,et al.  Automatic segmentation of thalamic nuclei from diffusion tensor magnetic resonance imaging , 2003, NeuroImage.

[66]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[67]  R. Poldrack,et al.  Microstructure of Temporo-Parietal White Matter as a Basis for Reading Ability Evidence from Diffusion Tensor Magnetic Resonance Imaging , 2000, Neuron.

[68]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[69]  Alan Barnett,et al.  Theory of Q‐ball imaging redux: Implications for fiber tracking , 2009, Magnetic resonance in medicine.

[70]  D Le Bihan,et al.  Human Subinsular Asymmetry Studied by Diffusion Tensor Imaging and Fiber Tracking , 2007, American Journal of Neuroradiology.

[71]  Baba C. Vemuri,et al.  Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT) , 2006, NeuroImage.

[72]  C. Westin,et al.  A method for clustering white matter fiber tracts. , 2006, AJNR. American journal of neuroradiology.

[73]  J. Sweeney,et al.  White matter integrity and cognition in chronic traumatic brain injury: a diffusion tensor imaging study. , 2007, Brain : a journal of neurology.

[74]  V. Haughton,et al.  Diffusion tensor MR imaging in diffuse axonal injury. , 2002, AJNR. American journal of neuroradiology.

[75]  S. Schoenberg,et al.  Measurement of signal‐to‐noise ratios in MR images: Influence of multichannel coils, parallel imaging, and reconstruction filters , 2007, Journal of magnetic resonance imaging : JMRI.

[76]  Larry A. Kramer,et al.  Diffusion tensor imaging-based tissue segmentation: Validation and application to the developing child and adolescent brain , 2007, NeuroImage.

[77]  P. Basser,et al.  Diffusion tensor MR imaging of the human brain. , 1996, Radiology.

[78]  Yaniv Assaf,et al.  Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain , 2005, NeuroImage.

[79]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[80]  D. Salat,et al.  Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[81]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[82]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[83]  J. Shimony,et al.  Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. , 2001, Radiology.

[84]  Christian Beaulieu,et al.  Diffusion tensor imaging of neurodevelopment in children and young adults , 2005, NeuroImage.